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A prototype 2007 ISL Cummins diesel engine equipped with a diesel oxidation catalyst (DOC), diesel particle filter (DPF), variable geometry turbocharger (VGT), and cooled exhaust gas recirculation (EGR) was tested at Southwest Research Institute (SwRI) under a high-load accelerated durability cycle for 1000 hours with B20 soy-based biodiesel blends and ultra-low sulfur diesel (ULSD) fuel to determine the impact of B20 on engine durability, performance, emissions, and fuel consumption. At the completion of the 1000-hour test, a thorough engine teardown evaluation of the overhead, power transfer, cylinder, cooling, lube, air handling, gaskets, aftertreatment, and fuel system parts was performed. The engine operated successfully with no biodiesel-related failures. Results indicate that engine performance was essentially the same when tested at 125 and 1000 hours of accumulated durability operation.

The emerging need of building an efficient Electric Vehicle (EV) charging infrastructure requires the investigation of all aspects of Vehicle-Grid Integration (VGI), including the impact of EV charging on the grid, optimal EV charging control at scale, and communication interoperability. This paper presents a cloud-based simulation and testing platform for the development and Hardware-in-the-Loop (HIL) testing of VGI technologies. Although the HIL testing of a single charging station has been widely performed, the HIL testing of spatially distributed EV charging stations and communication interoperability is limited. To fill this gap, the presented platform is developed that consists of multiple subsystems: a real-time power system simulator (OPAL-RT), ISO 15118 EV Charge Scheduler System (EVCSS), and a Smart Energy Plaza (SEP) with various types of charging stations, solar panels, and energy storage systems.

In order to reduce fuel consumption, companies have been looking at hybridizing vehicles. So far, two main hybridization options have been considered: electric and hydraulic hybrids. Because of light duty vehicle operating conditions and the high energy density of batteries, electric hybrids are being widely used for cars. However, companies are still evaluating both hybridization options for medium and heavy duty vehicles. Trucks generally demand very large regenerative power and frequent stop-and-go. In that situation, hydraulic systems could offer an advantage over electric drive systems because the hydraulic motor and accumulator can handle high power with small volume capacity. This study compares the fuel displacement of class 6 trucks using a hydraulic system compared to conventional and hybrid electric vehicles. The paper will describe the component technology and sizes of each powertrain as well as their overall vehicle level control strategies.

Modeling plume interaction and collapse for direct-injection gasoline sprays is important because of its impact on fuel-air mixing and engine performance. Nevertheless, the aerodynamic interaction between plumes and the complicated two-phase coupling of the evaporating spray has shown to be notoriously difficult to predict. With the availability of high-speed (100 kHz) Particle Image Velocimetry (PIV) experimental data, we compare velocity field predictions between plumes to observe the full temporal evolution leading up to plume merging and complete spray collapse. The target “Spray G” operating conditions of the Engine Combustion Network (ECN) is the focus of the work, including parametric variations in ambient gas temperature. We apply both LES and RANS spray models in different CFD platforms, outlining features of the spray that are most critical to model in order to predict the correct aerodynamics and fuel-air mixing.

Striving for sustainable transportation solutions, hydrogen is often identified as a promising energy carrier and internal combustion engines are seen as a cost effective consumer of hydrogen to facilitate the development of a large-scale hydrogen infrastructure. Driven by efficiency and emissions targets defined by the U.S. Department of Energy, a research team at Argonne National Laboratory has worked on optimizing a spark-ignited direct injection engine for hydrogen. Using direct injection improves volumetric efficiency and provides the opportunity to properly stratify the fuel-air mixture in-cylinder. Collaborative 3D-CFD and experimental efforts have focused on optimizing the mixture stratification and have demonstrated the potential for high engine efficiency with low NOx emissions. Performance of the hydrogen engine is evaluated in this paper over a speed range from 1000 to 3000 RPM and a load range from 1.7 to 14.3 bar BMEP.

A methodology has been developed for identifying the combination of battery characteristics which lead to least-cost electric vehicles. Battery interrelationships include specific power vs, specific energy, peak power vs. specific energy and DOD, cycle life vs. DOD, cost vs. specific energy and peak power, and volumetric and battery size effects. The method is illustrated for the “second car” mission assuming lead/acid batteries. Reductions in life-cycle costs associated with future battery research breakthroughs are estimated using a sensitivity technique. A research prioritization system is described.

The Modular Automotive Technology Testbed (MATT) is a flexible platform built to test different technology components in a vehicle environment. This testbed is composed of physical component modules, such as the engine and the transmission, and emulated components, such as the energy storage system and the traction motor. The instrumentation on the tool enables the energy balance for individual components on drive cycles. Using MATT, a single set of hardware can operate as a conventional vehicle, a hybrid vehicle and a plug-in hybrid vehicle, enabling direct comparison of petroleum displacement for the different modes. The engine provides measured fuel economy and emissions. The losses of components which vary with temperature are also measured.

Proper electric and thermal management of an HEV battery pack, consisting of many modules of cells, is imperative. During operation, voltage and temperature differences in the modules/cells can lead to electrical imbalances from module to module and decrease pack performance by as much as 25%. An active battery management system (BMS) is a must to monitor, control, and balance the pack. The University of Toledo, with funding from the U.S. Department of Energy and in collaboration with DaimlerChrysler and the National Renewable Energy Laboratory has developed a modular battery management system for HEVs. This modular unit is a 2nd generation system, as compared to a previous 1st generation centralized system. This 2nd generation prototype can balance a battery pack based on cell-to-cell measurements and active equalization. The system was designed to work with several battery types, including lithium ion, NiMH, or lead acid.

The goal of the automated mobility platforms (AMPs) initiative is to raise the bar of service regarding equity and sustainability for public mobility systems that are crucial to large facilities, and doing so using electrified, energy efficient technology. Using airports as an example, the rapid growth in air travel demand has led to facility expansions and congested terminals, which directly impacts equity (e.g., increased challenges for Passengers with Reduced Mobility [PRMs]) and sustainability—both of which are important metrics often overlooked during the engineering design process.

Accurate evaluation of vehicles' transient total power requirement helps achieving further improvements in vehicle fuel efficiency. When operated, the air-conditioning (A/C) system is the largest auxiliary load on a vehicle, therefore accurate evaluation of the load it places on the vehicle's engine and/or energy storage system is especially important. Vehicle simulation models, such as "Autonomie," have been used by OEMs to evaluate vehicles' energy performance. However, the load from the A/C system on the engine or on the energy storage system has not always been modeled in sufficient detail. A transient A/C simulation tool incorporated into vehicle simulation models would also provide a tool for developing more efficient A/C systems through a thorough consideration of the transient A/C system performance. The dynamic system simulation software MATLAB/Simulink® is frequently used by vehicle controls engineers to develop new and more efficient vehicle energy system controls.

Plug-in hybrid electric vehicle (PHEV) technologies have the potential for considerable petroleum consumption reductions, possibly at the expense of increased tailpipe emissions due to multiple “cold” start events and improper use of the engine for PHEV specific operation. PHEVs operate predominantly as electric vehicles (EVs) with intermittent assist from the engine during high power demands. As a consequence, the engine can be subjected to multiple cold start events. These cold start events may have a significant impact on the tailpipe emissions due to degraded catalyst performance and starting the engine under less than ideal conditions. On current hybrid electric vehicles (HEVs), the first cold start of the engine dictates whether or not the vehicle will pass federal emissions tests. PHEV operation compounds this problem due to infrequent, multiple engine cold starts.

Road vehicles can expend a significant amount of energy in undesirable vertical motions that are induced by road bumps, and much of that is dissipated in conventional shock absorbers as they dampen the vertical motions. Presented in this paper are some of the results of a study aimed at determining the effectiveness of efficiently transforming that energy into electrical power by using optimally designed regenerative electromagnetic shock absorbers. In turn, the electrical power can be used to recharge batteries or other efficient energy storage devices (e.g., flywheels) rather than be dissipated. The results of the study are encouraging - they suggest that a significant amount of the vertical motion energy can be recovered and stored.

The 4th Workshop of the Engine Combustion Network (ECN) was held September 5-6, 2015 in Kyoto, Japan. This manuscript presents a summary of the progress in experiments and modeling among ECN contributors leading to a better understanding of soot formation under the ECN “Spray A” configuration and some parametric variants. Relevant published and unpublished work from prior ECN workshops is reviewed. Experiments measuring soot particle size and morphology, soot volume fraction (fv), and transient soot mass have been conducted at various international institutions providing target data for improvements to computational models. Multiple modeling contributions using both the Reynolds Averaged Navier-Stokes (RANS) Equations approach and the Large-Eddy Simulation (LES) approach have been submitted. Among these, various chemical mechanisms, soot models, and turbulence-chemistry interaction (TCI) methodologies have been considered.

Battery second use-putting used plug-in electric vehicle (PEV) batteries into secondary service following their automotive tenure-has been proposed as a means to decrease the cost of PEVs while providing low cost energy storage to other fields (e.g., electric utility markets). To understand the value of used automotive batteries, however, we must first answer several key questions related to battery degradation, including: How long will PEV batteries last in automotive service? How healthy will PEV batteries be when they leave automotive service? How long will retired PEV batteries last in second-use service? How well can we best predict the second-use lifetime of a used automotive battery? Under the support of the U.S. Department of Energy's Vehicle Technologies Office, the National Renewable Energy Laboratory has developed a methodology and the requisite tools to answer these questions, including the Battery Lifetime Simulation Tool (BLAST).

This work presents a simple fan model that is based on the actuator disk approximation, and the blade element and vortex theory of a propeller. A set of equations are derived that require as input the rotational speed of the fan, geometric fan data, and the lift and drag coefficients of the blades. These equations are solved iteratively to obtain the body forces generated by the fan in the axial and circumferential directions. These forces are used as momentum sources in a CFD code to simulate the effect of the fan in an underhood thermal management simulation. To validate this fan model, a fan experiment was simulated. The model was incorporated into the CFD code STAR-CD and predictions were generated for axial and circumferential air velocities at different radial positions and at different planes downstream of the fan. The agreement between experimental measurements and predictions is good.

The objective of this work is to provide a relatively simple battery energy storage and loss model that can be used for technology screening and design/sizing studies of hybrid electric vehicle powertrains. The model dynamic input requires only power demand from the battery terminals (either charging or discharging), and outputs internal battery losses, state-of-charge (SOC), and pack temperature. Measured data from a vehicle validates the model, which achieves reasonable accuracy for current levels up to 100 amps for the size battery tested. At higher current levels, the model tends to report a higher current than what is needed to create the same power level shown through the measured data. Therefore, this battery model is suitable for evaluating hybrid vehicle technology and energy use for part load drive cycles.

Battery electric vehicles (BEVs) offer the potential to reduce both oil imports and greenhouse gas emissions, but high upfront costs, battery-limited vehicle range, and concern over high battery replacement costs may discourage potential buyers. A subscription model in which a service provider owns the battery and supplies access to battery swapping infrastructure could reduce upfront and battery replacement costs with a predictable monthly fee, while expanding BEV range. Assessing the costs and benefits of such a proposal are complicated by many factors, including customer drive patterns, the amount of required infrastructure, battery life, etc. The National Renewable Energy Laboratory has applied its Battery Ownership Model to compare the economics and utility of BEV battery swapping service plan options to more traditional direct ownership options.

Accelerated market penetration of plug-in electric vehicles (PEVs) is presently restricted by the high cost of batteries. Deployment of grid-connected energy storage, which could increase the reliability, efficiency, and cleanliness of the grid, is similarly inhibited by the cost of batteries. Research, development, and manufacturing are underway to reduce cost by lowering material costs, enhance process efficiencies, and increase production volumes. Another approach under consideration is to recover a fraction of the battery cost after the battery has been retired from vehicular service via reuse in other applications, where it may still have sufficient performance to meet the requirements of other energy-storage applications.

The application of Computational Fluid Dynamics (CFD) for three-dimensional (3D) combustion analysis coupled with detailed chemistry in engine development is hindered by its expensive computational cost. Chemistry computation may occupy as much as 90% of the total computational cost. In the present paper, a new two-step iso-octane combustion model was developed for spark-ignited (SI) engine to maximize computational efficiency while maintaining acceptable accuracy. Starting from the model constants of an existing global combustion model, the new model was developed using an approach based on sensitivity analysis to approximate the results of a reference skeletal mechanism. The present model involves only five species and two reactions and utilizes only one uniform set of model constants. The validation of the new model was performed using shock tube and real SI engine cases.

The Automotive Deployment Options Projection Tool (ADOPT) is a light-duty vehicle consumer choice and stock model supported by the U.S. Department of Energy's Vehicle Technologies Office. It estimates technology improvement impacts on future U.S. light-duty vehicles sales, petroleum use, and greenhouse gas emissions. ADOPT uses techniques from the multinomial logit method and the mixed logit method to estimate vehicle sales. Specifically, it estimate sales based on the weighted value of key attributes including vehicle price, fuel cost, acceleration, range and usable volume. The average importance of several attributes changes nonlinearly across its range and changes with income. For several attributes, a distribution of importance around the average value is used to represent consumer heterogeneity. The majority of existing vehicle makes, models, and trims are included to fully represent the market. The Corporate Average Fuel Economy regulations are enforced.